Introduction to Artificial Intelligence (3 cr)
Code: TT00EV75-3009
General information
- Timing
-
01.01.2025 - 31.12.2026
Implementation is running.
- Number of ECTS credits allocated
- 3 cr
- Virtual portion
- 3 cr
- Mode of delivery
- Online
- Unit
- (2019-2024) School of ICT
- Campus
- Karaportti 2
- Teaching languages
- English
- Seats
- 0 - 1000
- Degree programmes
- Information and Communication Technology
- Groups
-
AVOIN_AMK_TIVI_73_opComplementary Informatics past graduate degree
- Course
- TT00EV75
Objective
After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence in practise.
Content
- Introduction
- Data Exploration
- Supervised learning
- Unsupervised learning
- Deep Learning
- Reinforcement learning
Location and time
Course is delivered via Metropolia's Viope environment and it can be done in own pace.
Materials
All of course material is online in Metropolia's Viope.
Teaching methods
Course is 100% online (Self-Study) course and it can be done in own pace.
Employer connections
N/A
Exam schedules
N/A
International connections
N/A
Completion alternatives
N/A
Student workload
Course is self-study course, so, timetable is totally up to student her-/himself.
Content scheduling
Course is self-study course, so, student can schedule course her-/himself.
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Assessment methods and criteria
After student has done at least 80% of tasks he/she can get grade pass.
Objective
After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence in practise.
Content
- Introduction
- Data Exploration
- Supervised learning
- Unsupervised learning
- Deep Learning
- Reinforcement learning